Matsuyama City Rainfall Data Analysis Using Wavelet Transform

Santos, Celso Augusto Guimarães; Galvão, Carlos de Oliveira; Suzuki, Koichi; Trigo, Ricardo M.

doi:10.2208/prohe.45.211

Cited by 44 publications

(42 citation statements)

References 7 publications

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“…w 0 must be equal to or greater than 5 to satisfy the wavelet admissibility condition (Farge, 1992;Cromwell, 2001): the function must have zero mean and be localized in both time and frequency space to be "admissible" as a wavelet (Santos et al, 2001). In the present application, we use w 0 = 6, a value commonly used for geoscience applications Compo, 1998, Labat, 2005;Si and Zeleke, 2005;Schaefli and Zehe, 2009).…”

Section: Wavelet Transform Analyses On Water-level Time Seriesmentioning

confidence: 99%

Technical Note: Glacial influence in tropical mountain hydrosystems evidenced by the diurnal cycle in water levels

Cauvy‐Fraunié

Condom

Rabatel

et al. 2013

Hydrol. Earth Syst. Sci.

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Abstract. Worldwide, the rapid shrinking of glaciers in response to ongoing climate change is modifying the glacial meltwater contribution to hydrosystems in glacierized catchments. Determining the influence of glacial runoff to streams is therefore of critical importance to evaluate potential impact of glacier retreat on water quality and aquatic biota. This task has challenged both glacier hydrologists and ecologists over the last 20 yr due to both structural and functional complexity of the glacier-stream system interface. Here we propose quantifying the diurnal cycle amplitude of the streamflow to determine the glacial influence in glacierized catchments. We performed water-level measurements using water pressure loggers over 10 months at 30 min time steps in 15 stream sites in 2 glacier-fed catchments in the Ecuadorian Andes (> 4000 m a.s.l.) where no perennial snow cover is observed outside the glaciers. For each stream site, we performed wavelet analyses on water-level time series, determined the scale-averaged wavelet power spectrum at 24 h scale and defined three metrics, namely the power, frequency and temporal clustering of the diurnal flow variation. The three metrics were then compared to the percentage of the glacier cover in the catchments, a metric of glacial influence widely used in the literature. As expected, we found that the diurnal variation power of glacier-fed streams decreased downstream with the addition of non-glacial tributaries. We also found that the diurnal variation power and the percentage of the glacier cover in the catchment were significantly positively correlated. Furthermore, we found that our method permits the detection of glacial signal in supposedly non-glacial sites, thereby revealing glacial meltwater resurgence. While we specifically focused on the tropical Andes in this paper, our approach to determine glacial influence may have potential applications in temperate and arctic glacierized catchments. The measure of diurnal water amplitude therefore appears as a powerful and cost-effective tool to understand the hydrological links between glaciers and hydrosystems better and assess the consequences of rapid glacier shrinking.

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Section: Wavelet Transform Analyses On Water-level Time Seriesmentioning

confidence: 99%

Technical Note: Glacial influence in tropical mountain hydrosystems evidenced by the diurnal cycle in water levels

Cauvy‐Fraunié

Condom

Rabatel

et al. 2013

Hydrol. Earth Syst. Sci.

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show abstract

“…Wavelet analysis has advantage over other methods since it is able to identify temporal variability in the periodic nature of the time series as shown by Refs. [6,15,16]. While spectral analysis reduces information to ensemble averages, wavelet analysis technique categorizes the information in terms of time-frequency modes, decomposing the signals into localized oscillations and achievable through isolating short processes embedded in highly structured harmonic phenomena, analyze the progression of time signals or track the characteristics of an event or feature over a wide range of scales.…”

Section: Methodsmentioning

confidence: 99%

“…[2][3][4][5] have suggested that interannual variability of the oceanic stratification could modulate the SST signature of the MJO (Madden Jullien Oscillation) and may be both high and low frequency oscillations associated with MJO itself. Santos, C. A. G. et al [6] used wavelet transform using rainfall time series for studies concerning soil erosion and land degradation for runoff-erosion simulations.…”

Section: Introductionmentioning

confidence: 99%

Use of Wavelet Transform to Analyse Observed Precipitation at Bukoba, Tanzania to Recognize Impacts to Hydrological Response in Lake Victoria Basin

Tilya¹,

Sangalugembe²,

Kijazi³

2016

JGRE

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This research exploited seventy years of daily precipitation data from Bukoba, Tanzania to understand precipitation variability and change important for water resource management. Morlet Wavelet Transform was applied to discriminate the distinct time-frequency rainfall variability in the 92 days long MAM ((March and May)) and OND (October to December) primary rainfall seasons for intraseasonal characteristics over the periods 1931-1960, 1961-1990 and 1971-2000. The time-frequency analysis yielded wavelets outlining the intraseasonal nature of sporadic wet and dry spells in each epoch. The characters of the spells designate changing distribution, intensity and frequency of occurrence across the three epochs. The profile of the erratic wet and dry spells speculates shift change and fading of high frequency, quasi biweekly and low frequency oscillations. The oscillations which act together across atmosphere, oceans and land surfaces through convective processes are likely to influence seasonal precipitation anomalies at intraseasonal scale. The variability of the observed daily precipitation is thus hypothesized to be linked to the fading oscillations in the later two epochs particularly during the main MAM season and thus the declining precipitation in the study domain. Global increased atmospheric carbon dioxide concentration could catalyze this process.

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“…To solve this problem Wavelet Transform can be used, which transformed or decomposed a one dimensional time series into two diffusive time series simultaneously. Only then it is possible to get information from any periodic signals within the time series and how this time series varies over time [17].…”

Section: Datamentioning

confidence: 99%

Pattern Recognition of Rainfall Using Wavelet Transform in Bangladesh

Rahman¹,

Anik²,

Farhana³

et al. 2018

OJS

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The aim of the study is to explore the regional variation of changing patterns of rainfall in Bangladesh using wavelet transform. The study is completed using rainfall variation of the five regions of Bangladesh as Dhaka, Cox's Bazar, Rajshahi, Bogra and Sylhet. The duration of the study period was 69 years for Dhaka, 64 years for Cox's Bazar, 40 years for Rajshahi, 54 years for Bogra and 55 years for Sylhet. The results of the wavelet analysis reveals that, in Rajshahi the amount of rainfall are decreasing in a significant rate among the other study regions. It also explores the annual periodicity of rainfall for all the study regions along with a special 6-month periodicity in the Cox's Bazar. In addition, this analysis also explores a dominating 3 -4 year cycle of rainfall in all the study regions. Besides the climate change in Cox's Bazar and Sylhet are pretty much alarming.

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Matsuyama City Rainfall Data Analysis Using Wavelet Transform

Cited by 44 publications

References 7 publications

Technical Note: Glacial influence in tropical mountain hydrosystems evidenced by the diurnal cycle in water levels

Technical Note: Glacial influence in tropical mountain hydrosystems evidenced by the diurnal cycle in water levels

Use of Wavelet Transform to Analyse Observed Precipitation at Bukoba, Tanzania to Recognize Impacts to Hydrological Response in Lake Victoria Basin

Pattern Recognition of Rainfall Using Wavelet Transform in Bangladesh

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